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About Aviron
We are a team of problem-solvers and communicators. What does this mean for our clients? Not only are we going to accomplish your project, but you’re going to be informed and confident every step of the way. Our team of experts is passionate about fully understanding your problem, finding solutions, and getting it done. The right way.
If the top of your to-do list screams “hire software engineer!, ” we’d love the opportunity to talk about your goals and problem points.
Proven Software Consulting Services.
Increase in overall revenue after working with Aviron Software
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Insights
The Hidden Performance Costs of AI Features in React And How to Fix Them
AI features like smart autocompletion, chatbots, and content generation can elevate React apps but often introduce hidden performance costs. External API calls, heavy payloads, and frontend processing can slow down user experiences if not properly managed. This post explains why AI features can create latency, extra re-renders, and memory issues, and offers practical strategies to fix them. By using techniques like debouncing API calls, streaming responses, lazy loading components, offloading work to background workers, and caching AI results, React developers can build AI-powered apps that stay fast, efficient, and user-friendly.
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Go Over C#: The TypeScript Team’s Surprising but Practical Choice
When the TypeScript team announced they were porting the TypeScript compiler to Go, the decision stirred debate—especially among those expecting Microsoft to favor its own language, C#. However, the move wasn't about dismissing C#, but about choosing the most pragmatic tool for the job. Go offers language semantics that closely mirror TypeScript, making the transition smoother and more efficient, particularly in terms of performance. While C# is powerful, its object-oriented nature would require major restructuring. Ultimately, this wasn’t a rewrite but a performance-driven port, emphasizing engineering pragmatism over internal politics.
Is .NET A Good Platform For Building AI-Integrated Apps?
At Aviron Software, we’ve seen a surge in demand for AI-powered features—especially from .NET teams unsure whether they need to learn Python to keep up. Spoiler alert: you don’t. In this in-depth guide, we walk through building modern AI applications entirely in .NET, covering everything from basic HTTPS requests to advanced topics like Semantic Kernel, RAG, tool calling, and even model fine-tuning. Whether you're integrating OpenAI into your C# apps or exploring Microsoft.Extensions.AI, we break down the tools, trade-offs, and real-world lessons from our recent client work (plus a few GitHub samples to get you started). Yes, .NET is AI-ready—and here’s how to prove it.
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